• Journal of applied mathematics & informatics
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• 제26권5_6호
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• pp.911-923
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• 2008

The neural networks (NNs) simulation has been designed to simulate and predict the vortex wavelength ${\lambda}_x^*$, lateral vortex spacing ${\lambda}_y^*$, and normalized maximum vorticity at the vortex center near the wake of square cylinders with different corner radii. The system was trained on the available data of the three cases, although this data is very little. Therefore, we designed the system to work in automatic way for finding the best network that has the ability to have the best test and prediction. The proposed system shows an excellent agreement with that of an experimental data in these cases. The technique has been also designed to simulate the other distributions not presented in the training set and predicted them with effective matching.

• 대한기계학회논문집B
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• 제25권5호
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• pp.731-740
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• 2001

A numerical study on the quantitative analogy between the fully developed turbulent flow in a straight square duct rotating about an axis perpendicular to that of the duct and that in a stationary curved duct of square cross-section is carried out. In order to clarify the similarity of the two flows, dimensionless parameters K(sub)TR=Re(sup)1/4/√Ro and Rossby number, Ro, in a rotating straight duct flow were used as a set corresponding to K(sub)TC=Re(sup)1/4/√λ and curvature ratio, λ, in a stationary curved duct flow so that they have the same dynamical meaning as those of the fully developed laminar flows. For the large values of Ro or λ, it is shown that the flow field satisfies the asymptotic invariance property, that is, there are strong quantitative similarities between the two flows such as flow patterns and friction factors for the same values of K(sub)TR and K(sub)TC.

• Journal of the Korean Statistical Society
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• 제29권3호
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• pp.307-313
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• 2000

Suppose we have a set of data X1, ···, Xn and employ kernel density estimator to estimate the marginal density of X. in this article bandwith selection problem for kernel density estimator is examined closely. In particular the Kullback-Leibler method (a bandwith selection methods based on average square error (ASE)) is considered.

• 대한가정학회지
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• 제33권2호
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• pp.159-166
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• 1995

The purpose of the present study is to investigate how closely care labels comply with the 1984 version of the Care Labeling Rule, as well as the change in degree of compliance prior to and after the 1988 IFI care label campaign. Label information was analyzed on the basis of country of origin. The information was also divided into two sets. The basis for dividing the data into two sets was the beginning of the IFI care label campaign in 1988 The data were obtained from 1147 checklists. The information for 1147 samples in six clothing categories were collected from department, specialty, and discount stores. Chi-square analyses were conducted to test hypotheses. While there was no significant difference in the number of incorrect labels on domestically produced garments compared to imported garments in set 1, there was a significant difference in set 2. Also, there was a significnat differnece in the number of incorrect labels between in set 1 and in set 2.

• 설비공학논문집
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• 제18권11호
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• pp.896-905
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• 2006

An optimal control of an air-conditioning system with slab thermal storage is investigated by making use of the Maximum Principle. An optimal heat input to a plenum chamber and an air-conditioned room is determined by minimizing a criterion function which is given as integral sum of two terms. The first term is the square of the deviation in the room air temperature from the set-point value, and the second is the absolute value of the heat input. The result indicates that it tries to keep a room air temperature in set-point value by heating as much as possible at the time of a setup of a room air temperature or just before that, in order to avoid a heat loss arising at the time of the non-air conditioning. The result is compared with that of the case when the square of the heat input is used as a criterion.

• 한국임상수의학회지
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• 제27권4호
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• pp.427-434
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• 2010

Correlation is a technique used to measure the strength or the degree of closeness of the linear association between two quantitative variables. Common misuses of this technique are highlighted. Linear regression is a technique used to identify a relationship between two continuous variables in mathematical equations, which could be used for comparison or estimation purposes. Specifically, regression analysis can provide answers for questions such as how much does one variable change for a given change in the other, how accurately can the value of one variable be predicted from the knowledge of the other. Regression does not give any indication of how good the association is while correlation provides a measure of how well a least-squares regression line fits the given set of data. The better the correlation, the closer the data points are to the regression line. In this tutorial article, the process of obtaining a linear regression relationship for a given set of bivariate data was described. The least square method to obtain the line which minimizes the total error between the data points and the regression line was employed and illustrated. The coefficient of determination, the ratio of the explained variation of the values of the independent variable to total variation, was described. Finally, the process of calculating confidence and prediction interval was reviewed and demonstrated.

• 한국정보과학회논문지:시스템및이론
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• 제32권8호
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• pp.411-417
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• 2005

본 논문에서는 입력으로 주어진 점집차 (point cloud)으로부터 캐널곡면을 복원 (reconstruction)하는 알고리즘을 제시한다. 캐널곡면은 반경이 변화하며 중심점이 기준곡선(spine curve)을 따라 이동하는 구(moving sphere)의 스웹트곡면(swept surface)이다. 이 논문에서는 수축기법(shrinking method)과 moving least-square 방법을 이용하여 주어진 점집합을 세곡선(thin-curve)형태의 점집합으로 수축시킴으로써 캐널곡면의 기준곡선을 근사한다. 근사된 기준곡선과 입력으로 주어진 점집합에 포함된 점들 사이의 거리를 이용하여, 캐널곡면을 구성하는 이동 구의 반경을 계산한다.

• 한국의류산업학회지
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• 제21권2호
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• pp.163-170
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• 2019

This study utilized the wearing test of subjects and a preference survey to determine wearing preference on types of blouses according to shoulder angle. The shoulder angles of the subjects were set as average shoulder, slopping shoulder, and square shoulder. The blouse sleeves were set as set-in, raglan, and kimono according to five domestic clothing construction books. A total of 15 blouses were made and tested by different bodices and sleeve types. The wearing test of subjects had the human subjects evaluate the appearance of the subject looking at the mirror while standing as well as evaluated the sensation test while not looking at the mirror. The preference survey was given to 100 females and was conducted using photos with combinations of three types of sleeves and shoulder angles in a survey under the same conditions. The average shoulder showed that set-in with the highest score in the wearing test was also preferred in the preference survey. The slopping shoulder evaluated the highest score in the wearing test by mirror; however, the preference survey showed that raglan was the most preferred choice. The squared shoulder showed that raglan with a high score in the wearing test by mirror was also preferred in the preference survey.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.155-157
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• 2005

We propose a new category of hybrid multi-layer neural networks with hetero nodes such as Fuzzy Set based Polynomial Neurons (FSPNs) and Polynomial Neurons (PNs). These networks are based on a genetically optimized multi-layer perceptron. We develop a comprehensive design methodology involving mechanisms of genetic optimization and genetic algorithms, in particular. The augmented genetically optimized HFPNN (namely gHFPNN) results in a structurally optimized structure and comes with a higher level of flexibility in comparison to the one we encounter in the conventional HFPNN. The GA-based design procedure being applied at each layer of HFPNN leads to the selection of preferred nodes (FPNs or PNs) available within the HFPNN. In the sequel, two general optimization mechanisms are explored. First, the structural optimization is realized via GAs whereas the ensuing detailed parametric optimization is carried out in the setting of a standard least square method-based learning. The performance of the gHFPNNs quantified through experimentation where we use a number of modeling benchmarks-synthetic and experimental data already experimented with in fuzzy or neurofuzzy modeling.

• 한국통신학회논문지
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• 제22권4호
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• pp.662-674
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• 1997

In order to post process the vector-quantized images employing the theory of projections onto convex sets or the constrained minimization technique, the the projector onto QCS(quantization constraint set) as well as the filter that smoothes the lock boundaries should be investigated theoretically. The basic idea behind the projection onto QCS is to prevent the processed data from diverging from the original quantization region in order to reduce the blurring artifacts caused by a filtering operation. However, since the Voronoi regions in order to reduce the blurring artifacts caused by a filtering operation. However, since the Voronoi regions in the vector quantization are arbitrarilly shaped unless the vector quantization has a structural code book, the implementation of the projection onto QCS is very complicate. This paper mathematically analyzes the projection onto QCS from the viewpoit of minimizing the mean square error. Through the analysis, it has been revealed that the projection onto a subset of the QCS yields lower distortion than the projection onto QCS does. Searching for an optimal constraint set is not easy and the operation of the projector is complicate, since the shape of optimal constraint set is dependent on the statistical characteristics between the filtered and original images. Therefore, we proposed a hyper-cube as a constraint set that enables a simple projection. It sill be also shown that a proper filtering technique followed by the projection onto the hyper-cube can reduce the quantization distortion by theory and experiment.